Archives: Publications

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  Marchal-Crespo, Laura; Novak, Domen; Lambercy, Olivier; Gassert, Roger; Riener, Robert

Individuals with severe neurologic injuries often cannot participate in robotic rehabilitation because they do not retain sufficient residual motor control to initiate the robotic assistance. In these situations, brain- and body-computer interfaces have emerged as promising solutions to control robotic devices. In a previous experiment conducted with healthy subjects, we showed that detecting motor execution accurately was possible using only the autonomic nervous system (ANS) response. In this paper, we investigate the feasibility of such a body–machine interface to detect motion intention by monitoring the ANS response in stroke survivors. Four physiological signals were measured (blood pressure, breathing rate, skin conductance response and heart rate) while participants executed and imagined a grasping task with their impaired hand. The physiological signals were then used to train a classifier based on hidden Markov models. We performed an experiment with four chronic stroke survivors to test the effectiveness of the classifier to detect rest, motor execution and motor imagery periods. We found that motion execution can be accurately classified based only on peripheral autonomic signals with an accuracy of 72.4%. The accuracy of classifying motion imagery was 62.4%. Therefore, attempting to move was a more effective strategy than imagining the movement. These results are encouraging to perform further research on the use of the ANS response in body-machine interfaces.

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  Isler, Stefan; Sabzevari, R.; Delmerico, J.; Scaramuzza, D.

We consider the problem of next-best view selection for volumetric reconstruction of an object by a mobile robot equipped with a camera. Based on a probabilistic volumetric map that is built in real time, the robot can quantify the expected information gain from a set of discrete candidate views. We propose and evaluate several formulations to quantify this information gain for the volumetric reconstruction task, including visibility likelihood and the likelihood of seeing new parts of the object. These metrics are combined with the cost of robot movement in utility functions. The next best view is selected by optimizing these functions, aiming to maximize the likelihood of discovering new parts of the object. We evaluate the functions with simulated and real world experiments within a modular software system that is adaptable to other robotic platforms and reconstruction problems. We release our implementation open source

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  Nycz, Christopher J.; Bützer, Tobias; Lambercy, Oliver; Arata, Jumpei; Fischer, Gregory S.; Gassert, Roger

Enabling individuals who are living with reduced mobility of the hand to utilize portable exoskeletons at home has the potential to deliver rehabilitation therapies with a greater intensity and relevance to activities of daily living. Various hand exoskeleton designs have been explored in the past, however, devices have remained nonportable and cumbersome for the intended users. Here we investigate a remote actuation system for wearable hand exoskeletons, which moves weight from the weakened limb to the shoulders, reducing the burden on the user and improving portability. A push-pull Bowden cable was used to transmit actuator forces from a backpack to the hand with strict attention paid to total system weight, size, and the needs of the target population. We present the design and integration of this system into a previously presented hand exoskeleton, as well as its characterization. Integration of remote actuation reduced the exoskeleton weight by 56% to 113g without adverse effects to functionality. Total actuation system weight was kept to 754g. The loss of positional accuracy inherent with Bowden cable transmissions was compensated for through closed loop positional control of the transmission output. The achieved weight reduction makes hand exoskeletons more suitable to the intended user, which will permit the study of their effectiveness in providing long duration, high intensity, and targeted rehabilitation as well as functional assistance.

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  Horvat, Tomislav; Karakasiliotis, Konstantinos; Melo, Kamilo; Fleury, Laura; Thandiackal, Robin; Ijspeert, Auke J.

Search and rescue (SAR) missions are being carried out by several types of robots. They include ground, marine and air vehicles depending on the terrain and mission to be tackled. A particular niche for SAR activities are shallow waters. They present high difficultly for conventional ground or marine robots because of the mix of water and ground. Such an environment is difficult to be accessed for a robot without some built-in amphibious capabilities. Our lab has experience in the design of amphibious salamander-like robots. In order to consider whether these robots would be suited for SAR missions in shallow waters, a key requirement is the ability to tackle rough terrains. In this paper we present a control framework for a highly redundant salamander-like robot. It involves bio-inspired spine control, inverse kinematics-based limb control, proper limb-spine coordination, reflex mechanisms and attitude control. The framework is validated in a simulation and on the real robot. In both cases, the robot is used in two different configurations: with and without its tail, in order to investigate how the tail (which is necessary for swimming) affects ground locomotion. With this exploration, we aim to set the precedent for improving the problem of dynamic locomotion of salamander-like robots over unperceived rough terrain. Our results confirm that the design of reflexes like stumbling and extension, combined with an attitude controller, allows for the improving of the performance of the robot in a generic rough terrain which includes stairs, holes and bumps with several levels of complexity adjusted according to the robot dimensions.

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  Wenger, Nikolaus; Moraud, Eduardo Martin; Gandar, Jérôme; Musienko, Pavel; Capogrosso, Marco; Baud, Laetitia; Le Goff, Camille G; Barraud, Quentin; Pavlova, Natalia; Dominici, Nadia; Minev, Ivan R; Asboth, Leonie; Hirsch, Arthur; Duis, Simone; Kreider, Julie; Mortera, Andrea; Haverbeck, Oliver; Kraus, Silvio; Schmitz, Felix; Digiovanna, Jack; Van Den Brand, Rubia; Bloch, Jocelyne; Detemple, Peter; Lacour, Stéphanie P; Bézard, Erwan; Micera, Silvestro; Courtine, Grégoire

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited the therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here we developed stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real-time control software that modulate extensor and flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight-bearing capacity, endurance and skilled locomotion in several rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans.

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  Moraud, Eduardo Martin; Capogrosso, Marco; Formento, Emanuele; Wenger, Nikolaus; Digiovanna, Jack; Courtine, Grégoire; Micera, Silvestro

Epidural electrical stimulation of lumbar segments facilitates standing and walking in animal models and humans with spinal cord injury. However, the mechanisms through which this neuromodulation therapy engages spinal circuits remain enigmatic. Using computer simulations and behavioral experiments, we provide evidence that epidural electrical stimulation interacts with muscle spindle feedback circuits to modulate muscle activity during locomotion. Hypothesis-driven strategies emerging from simulations steered the design of stimulation protocols that adjust bilateral hindlimb kinematics throughout gait execution. These stimulation strategies corrected subject-specific gait and balance deficits in rats with incomplete and complete spinal cord injury. The conservation of muscle spindle feedback circuits across mammals suggests that the same mechanisms may facilitate motor control in humans. These results provide a conceptual framework to improve stimulation protocols for clinical applications.